Abstract/Description

At present, wireless sensor networks and radio frequency identification (RFID) are both emerging technologies with great potential in seamless applications. Integrating these two technologies would provide low-cost solution for object identification and tracking for wide range of applications where, object and location awareness is crucial and essential.

Healthcare is one of the industries, where object and location aware applications are most wanted, particularly in enhancing patient safety and reducing medical errors by patient identification (Murphy & Kay, 2004). Unfortunately, healthcare environment is challenging, where radio interferences are restricted and IT literacy of the staffs are limited. It gets further challenging in convincing patients of their privacy and ethical issues that surrounds patient tagging and monitoring.

The aim of this project is to review methods involved in object identification and tracking in wireless sensor networks and to design and implement a prototype of wireless enabled framework for object identification and tracking. It is to mainly address the needs of healthcare and other similar environments. This project is perused in collaboration with National Health Service (NHS) - University Hospital Birmingham (UHB), Napier University, ConnectRFID and other industry partners. Based on onsite observation of IT infrastructure, and patient identification problems in hospital environment at UHB/NHS, a framework for object identification and location tracking is designed, implemented and benchmarked. It is developed using state-of-the-art tools and technologies in Visual Studio .NET, C#, MS SQL Server and ZPL for a variety of suitable equipments chosen to achieve the needs of this system. To evaluate, the framework is benchmarked for the limitations and performance using extensive logging of all activities and round trip times within parts of the framework. The database involved is also monitored and measured for its size in comparison with the number of activities within the framework.

The main outcome of this project is a state-of-the-art framework that suits the needs of object identification and tracking within healthcare environment. With minor changes the framework can be implemented in wide range object and location aware application and solutions. Two novel achievement of this work is, the framework is applied for patent protection (Patents, 2006) by NHS MidTECH on behalf UHB NHS and Napier University and contributed to writing and acceptance of a paper in International Journal of Healthcare Technology and Management (Thuemmler et al., 2007).